Since many epidemiologic problems cannot be solved by standard techniques, new methods can help extract more complete answers from research data. The objective of this project is to use mathematical theory and computer simulations to develop and evaluate statistical methods appropriate to data arising in epidemiologic research, and to carry out the statistical programming needed to make these methods easily available to other researchers. This may include evaluating outside computer software, using standard programs in novel ways, and writing special purpose programs. Further study will continue in the use of generalized linear models and the SAS procedure GLM in regression, analysis of variance, and analysis of covariance. Special interest will be paid to the use of logistic regression, log-linear models, and covariate adjustment using empirical Bayes techniques. Useful techniques will be presented in seminars and publications in statistical journals.